Course overview
- Study period
- Semester 2, 2025 (28/07/2025 - 22/11/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Mech & Mine Engineering School
This course explores the principles and practices of material selection for mechanical design, covering structural requirements, shape considerations, as well as economic and environmental impacts. Students will utilise material databases, material indices, and selection charts to make informed decisions. Through a practical project, students will gain hands-on experience in material selection tailored for real-world applications.
Engineering is the art of creation, where skilled engineers utilise raw materials to craft incredible things. From soaring skyscrapers to intricate machines, engineers shape the world around us and enhance our life through their creation. However, at the core of all engineering endeavours lies a crucial element that holds the key to success: material selection.
In this course, we'll dive into the world of material selection in engineering design. You will acquire the knowledge and skills to make methodical and intelligent decisions about what materials to use. These decisions are crucial, as they can have a significant impact on safety, performance, functionality, durability, cost, sustainability and ultimately the success of your designs.
The main goal of this course is to equip you with the knowledge and skills to effectively select materials, using the Materials Indices method,ﾠas an integral part of the engineering design process. You will gain the ability to systematically assess and compare candidate materials based on their properties. This approach empowers you to make informed decisions, resulting in optimal material selection that aligns with the desired engineering objectives.
Traditional methods of Materials Selection rely on extensive use of tables of material properties and experience, and therefore are largely empirical and can become cumbersome in practice. This method focuses on identifying the combination of material properties that maximises the engineering performance across various aspects, such as mechanical, thermal, and optical properties, as well as cost and sustainability, for a specific application.ﾠFor instance, when considering a tie rod subjected to tensile loading, the material that minimises its mass while maintaining the desired stiffness would be identified by maximising the elastic modulus/density ratio. This ratio, known as the Material Index for the tie rod, serves as a valuable tool for ranking candidate materials. Essentially, the most suitable material for the application is the one that provides the highest value of GPa per kg or the largest Index.
The material selection conducted through this approach is based on mathematical criteria, ensuring an unambiguous decision-making process. This method enables the selection of materials for structural applications by considering not only their inherent properties but also incorporating considerations of shape. Additionally, the method facilitates material substitutions while addressing multiple and potentially conflicting constraints. For instance, it allows for the identification of materials to make the design both cost-effective and lightweight. While the primary focus of the method is on structural applications, it also encompasses a broader range of physical properties, such as optical and thermal properties. Moreover, the method takes into account factors like price and sustainability, recognising their significance in the modern design process.
The course is structured around a series of lectures that introduceﾠthe selection method, providing a solid foundation for understanding the concept. A significant portion of the final marks is allocated to the resolution of the problem-based question set during the Applied Classes, with valuable guidance and support provided by the dedicated teaching team. These exercises are solved with the help of a dedicated software package, Granta CES Edupack 2021 (ANSYS), available in the faculty computer lab for the applied classes, and in all computer labs across the Faculty, allowing students to work on their assignments at any convenient time. Furthermore, a laboratory project is integrated into the course, aimed at familiarising students with the analysis of raw material data and the complete process of material selection in engineering design. By engaging in this hands-on experience, students gain a deeper understanding of the material selection process and its practical application. This experiential learning opportunity allows students to apply their knowledge and skills in real-world scenarios, further enhancing their grasp of material selection and its significance in engineering design.
Course requirements
Assumed background
ﾠBasic knowledge of mechanics and materials
Prerequisites
You'll need to complete the following courses before enrolling in this one:
MATE1000, ENGG1200, ENGG1211 or ENGG1700.
Incompatible
You can't enrol in this course if you've already completed the following:
MECH4301
Course contact
Course staff
Lecturer
Dr Mingyuan Lu
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
This course aims to introduce students to a systematic procedure for selecting materials that are best suited for a given engineering application, and to develop their proficiency in deriving material indices based on the relevant equations that describe the specific application. Additionally, the course aims to equip students with the skills necessary to successfully execute a simple mechanical design project. This involves tasks such as identifying the relevant material properties, selecting suitable candidates, and providing justified analysis in a technical report to support recommendations. Through these activities, students will gain hands-on experience and practical knowledge that will enhance their understanding of materials selection and their ability to apply it effectively in real-world engineering scenarios.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Tutorial/ Problem Set | Applied Class (5 assignments) | 45% |
Assignment 1 (5%) 19/08/2025 4:00 pm Assignment 2 (10%) 2/09/2025 4:00 pm Assignment 3 (10%) 23/09/2025 4:00 pm Assignment 4 (10%) 14/10/2025 4:00 pm Assignment 5 (10%) 31/10/2025 4:00 pm |
| Paper/ Report/ Annotation | Practical - Material Selection for Bicycle Forks (report) | 15% |
10/10/2025 4:00 pm |
| Examination |
Final Exam
|
40% |
End of Semester Exam Period 8/11/2025 - 22/11/2025 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Applied Class (5 assignments)
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 45%
- Due date
Assignment 1 (5%) 19/08/2025 4:00 pm
Assignment 2 (10%) 2/09/2025 4:00 pm
Assignment 3 (10%) 23/09/2025 4:00 pm
Assignment 4 (10%) 14/10/2025 4:00 pm
Assignment 5 (10%) 31/10/2025 4:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
The question sheet will be published in Blackboard before the Applied Class. You will be solving the problem-based questions with the help of the teaching team. The answers will be published in Blackboard a few days after the due day.
A1: Use of Materials Selection Charts (weight: 5%)
A2: Material Indices (weight: 10%)
A3: Materials and Shape (weight: 10%)
A4: Multiple Constraints & conflicting objectives (weight: 10%)
A5: Hybrid Materials (weight: 10%)
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Submission of these assessment items must be through TurnItIn via Blackboard site to detect any possibilities of plagiarism or collusion with another student(s) or existing documents.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Feedback released to students after this time, and avoids overlap into next exercise.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Practical - Material Selection for Bicycle Forks (report)
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 15%
- Due date
10/10/2025 4:00 pm
- Learning outcomes
- L01, L02, L03
Task description
Materials Selection Project completed in pairs.
See details in Blackboard, Folder Laboratory Project.
If, for whatever reason, you find that your group is not functioning effectively, please contact your Course Coordinator for support.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Submit via TurnItIn on Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Feedback released to students after this time.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Final Exam
- Hurdle
- Identity Verified
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
8/11/2025 - 22/11/2025
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
The Final Exam normally consists of a set of questions involving short derivations of material indices and the use of charts, and one or two exercises on Materials Selection related to existing components of, e.g., cars, aeroplanes, home appliances, bridges, musical instruments, sport goods, etc. (See examples of past exams at the library: https://www.library.uq.edu.au/exams/search.html).
Hurdle requirements
Identity verified assessment (IVA) will be through obtaining at least 40% of the available marks in the final exam. You need to pass the IVA hurdle to pass the course regardless of your final mark. Students who achieve a total mark of 50 or greater but do not pass the IVA hurdle will receive a grade of 3.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed book examination - specified written materials permitted |
| Materials | Hardcover Textbook: Ashby, M. F., Materials Selection in Mechanical Design, 4th and 5th edition. |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0.00 - 29.99 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30.00 - 44.99 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 45.00 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Falls short of satisfying basic requirements for a Pass. Overall grade: 45.00-49.99% or less that 40% in the IVA requirement explained below. |
| 4 (Pass) | 50.00 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Satisfies all of the basic learning requirements for the course, such as knowledge of fundamental concepts and performance of basic skills; demonstrates sufficient quality of performance to be considered satisfactory or adequate or competent or capable in the course. Overall grade 50.00-64.99% and a minimum score of 40% in the IVA requirement explained below. |
| 5 (Credit) | 65.00 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Demonstrates ability to use and apply fundamental concepts and skills of the course, going beyond mere replication of content knowledge or skill to show understanding of key ideas, awareness of their relevance, some use of analytical skills, and some originality or insight. Overall grade 65.00-74.99% and a minimum score of 40% in the IVA requirement explained below. |
| 6 (Distinction) | 75.00 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Demonstrates awareness and understanding of deeper and subtler aspects of the course, such as ability to identify and debate critical issues or problems, ability to solve non-routine problems, ability to adapt and apply ideas to new situations, and ability to invent and evaluate new ideas. Overall grade 75.00-84.99% and a minimum score of 40% in the IVA requirement explained below. |
| 7 (High Distinction) | 85.00 - 100.00 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Demonstrates imagination, originality or flair, based on proficiency in all the learning objectives for the course; work is interesting or surprising or exciting or challenging or erudite. Overall grade 85.00-100% and a minimum score of 40% in the IVA requirement explained below. |
Additional course grading information
Identity verified assessment.
Identity verified assessment (IVA) will be through obtainingﾠ at least 40% of the available marks in the final exam.
You need to pass the IVA hurdle to pass the course regardless of your final mark. Students who achieve a total mark of 50 or greater but do not pass the IVA hurdle will receive a grade of 3.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
A dedicated software package and associated database will be used for most of the exercises. The ﾠsoftware package, Granta CES Edupack 2021 (ANSYS), isﾠ available in the Computer Lab 78-328 for the Applied Classes. It is also ﾠavailable in all computer labs across the Faculty.ﾠ
Personal copies of the CES can be downloaded at http://student.eait.uq.edu.au/software/ces/
Lecture notes, exercises and other files relevant to the course, as well as materials selection charts, are or will be available as PDF files in Blackboard.ﾠ https://learn.uq.edu.au/ﾠ
Students can access the required UQ Laboratory Induction information on Blackboard.
The textbook (only the 4th edition) is available on line at UQ's Library's website linked in "Library resources". Hardcopies can be ordered at the Bookstore.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Watch lecture recording The one hour lecture will cover the concepts, methodologies, formulations of material indices and case studies. Learning outcomes: L01, L02, L03, L04, L05, L06, L07 |
Applied Class |
Solving assignment questions The teaching team will provide in-class consultation, give demonstrations on the use of the CES software and provide guidance for solving the questions. Learning outcomes: L01, L02, L03, L04, L05, L06, L07 |
|
Week 3 (11 Aug - 17 Aug) |
Lecture |
Introduction to the lab project (watch lecture recording) Introduction to Laboratory project. The lecture recording will be released a week prior to the start of the first prac session. Learning outcomes: L01, L02, L03 |
Multiple weeks From Week 4 To Week 6 |
Practical |
Project-material selection for bicycle forks You will only need to attend one of the 3 prac sessions in a team of two. You are required to submit a project report with your partner. Learning outcomes: L01, L02, L03 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
You'll also need to be aware of the following policies and procedures while completing this course:
- Laboratory Occupational Health and Safety